Exploring Chemical Concepts Through Theory and Computation provides a comprehensive account of how the three widely used theoretical frameworks of valence bond theory, molecular orbital theory, and density functional theory, along with a variety of important chemical concepts, can between them describe and efficiently and reliably predict key chemical parameters and phenomena. By comparing the three main theoretical frameworks, readers will become competent in choosing the right modeling approach for their task.
The authors go beyond a simple comparison of existing algorithms to show how data-driven theories can explain why chemical compounds behave the way they do, thus promoting a deeper understanding of the essence of chemistry. The text is contributed to by top theoretical and computational chemists who have turned computational chemistry into today’s data-driven and application-oriented science.
Exploring Chemical Concepts Through Theory and Computation discusses topics including: - Orbital-based approaches, density-based approaches, chemical bonding, partial charges, atoms in molecules, oxidation states, aromaticity and antiaromaticity, and acidity and basicity- Electronegativity, hardness, softness, HSAB, sigma-hole interactions, charge transport and energy transfer, and homogeneous and heterogeneous catalysis- Electrophilicity, nucleophilicity, cooperativity, frustration, homochirality, and energy decomposition- Chemical concepts in solids, excited states, spectroscopy and machine learning, and catalysis and machine learning, as well as key connections between related concepts
Aimed at both novice and experienced computational, theoretical, and physical chemists, Exploring Chemical Concepts Through Theory and Computation is an essential reference to gain a deeper, more advanced holistic understanding of the field of chemistry as a whole.
Table of Contents
Preface xv
Foreword xvii
10 Questions About Exploring Chemical Concepts Through Theory and Computation xix
1 Chemical Concepts from Molecular Orbital Theory 1
Feng Long Gu, Jincheng Yu, and Weitao Yang
1.1 Introduction 1
1.2 Molecular Orbital Theory 2
1.3 Canonical Molecular Orbitals 5
1.4 Frontier Molecular Orbital Theory 5
1.5 Localized Molecular Orbitals 6
1.6 Regularized Nonorthogonal Localized Molecular Orbitals 11
1.7 Molecular Orbitalets 15
2 Chemical Concepts from Ab Initio Valence Bond Theory 23
Chen Zhou, Fuming Ying, and Wei Wu
2.1 Introduction 23
2.2 Ab Initio Valence Bond Theory 24
2.3 Chemical Concepts in VB Theory 31
2.4 A Brief Guide to Perform VB Calculations 36
2.5 Concluding Remarks 38
3 Chemical Concepts from Conceptual Density Functional Theory 43
Frank De Proft
3.1 Introduction 43
3.2 The Fundamentals: Density Functional Theory (DFT) and Kohn-Sham DFT 46
3.3 The First Derivatives: The Electronic Chemical Potential and the Electron Density 48
3.4 The Second Derivatives: Chemical Hardness, Fukui Function, Linear Response Function, and Related Quantities 51
3.5 Perturbational Perspective of Chemical Reactivity 62
3.6 Conclusions 64
4 Chemical Concepts from Density-Based Approaches in Density Functional Theory 71
Dongbo Zhao, Xin He, Chunying Rong, and Shubin Liu
4.1 Introduction 71
4.2 Four Density-Based Frameworks 72
4.3 Applications of Density-Based Approaches 79
4.4 Concluding Remarks 94
5 Chemical Bonding 101
Sudip Pan and Gernot Frenking
5.1 Introduction 101
5.2 The Physical Mechanism of the Chemical Bond 103
5.3 Bonding Models 108
5.4 Bond Length and Bond Strength 111
5.5 Dative and Electron-Sharing Bonds 120
5.6 Polar Bonds 124
5.7 Atomic Partial Charges and Atomic Electronegativity 130
5.8 Chemical Bonding in Main-Group Compounds: N2, CO, BF, LiF 131
5.9 Chemical Bonding of the Heavier Main-Group Atoms 135
5.10 Chemical Bonding in Transition Metal Complexes: M(CO)n (M = Ni, Fe, Cr, Ti, Ca; n = 4 - 8) 143
5.11 Summary 146
6 Partial Charges 161
Tian Lu and Qinxue Chen
6.1 Concept of Partial Charge 161
6.2 Methods of Calculating Partial Charges 166
6.3 Partial Charges of Typical Molecules 176
6.4 Computer Codes for Evaluating Partial Charges 179
6.5 Concluding Remarks 180
7 Atoms in Molecules 189
Ángel Martín Pendás, Evelio Francisco, Julen Munárriz, and Aurora Costales
7.1 Introduction 189
7.2 The Quantum Theory of Atoms in Molecules (QTAIM) 190
7.3 QTAIM Atoms as Open Quantum Systems 194
7.4 Interacting Quantum Atoms (IQA) 200
8 Effective Oxidation States Analysis 207
Pedro Salvador
8.1 The Concept of Oxidation State 207
8.2 Oxidation State is Not Related to the Partial Charge 208
8.3 The Molecular Orbital Picture of the Ionic Approximation 210
8.4 Spin-Resolved Effective Fragment Orbitals and Effective Oxidation States (EOS) Analysis 213
8.5 EOS Analysis from Different AIM Schemes 216
8.6 Summary 220
9 Aromaticity and Antiaromaticity 223
Yago García-Rodeja and Miquel Solà
9.1 Definition of Aromaticity 223
9.2 Physical Foundation 224
9.3 Measures of Aromaticity 226
9.4 Rules of Aromaticity 233
9.5 Metallabenzenes and Related Compounds as an Example 239
10 Acidity and Basicity 251
Ranita Pal, Himangshu Mondal, and Pratim K. Chattaraj
10.1 Introduction 251
10.2 Definitions and Theories 252
10.3 CDFT-Based Reactivity Descriptors 257
10.4 CDFT-Based Electronic Structure Principles 259
10.5 Systemics of Lewis Acid-Base Reactions: Drago-Wayland Equation 261
10.6 Strengths of Acid and Bases 262
10.7 Effect of External Perturbation 267
10.8 CDFT and Acidity 270
10.9 CDFT and ITA 272
10.10 Are Strong Brønsted Acids Necessarily Strong Lewis Acids? 276
10.11 Summary 278
11 Sigma Hole Supported Interactions: Qualitative Features, Various Incarnations, and Disputations 285
Kelling J. Donald
11.1 Introduction 285
11.2 Many Incarnations and Roles of a Single Phenomenon 288
11.3 Related Interactions Elsewhere in the Main Group 304
11.4 Contested Interpretations 308
11.5 Conclusions 308
12 On the Generalization of Marcus Theory for Two-State Photophysical Processes 317
Chao-Ping Hsu and Chou-Hsun Yang
12.1 Introduction 317
12.2 The Golden Rule Rate Expression 318
12.3 Application 325
12.4 Conclusion 330
13 Computational Modeling of CO2 Reduction and Conversion via Heterogeneous and Homogeneous Catalysis 335
Yue Zhang, Lin Zhang, Denghui Ma, Xinrui Cao, and Zexing Cao
13.1 Introduction 335
13.2 Computational Methods 336
13.3 Activation and Reduction of CO2 338
13.4 Catalytic Coupling of CO2 with CH4 345
13.5 Homogeneous Catalytic Conversion of CO2 348
13.6 Conclusion and Outlook 352
14 Excited States in Conceptual DFT 361
Frédéric Guégan, Guillaume Hoffmann, Henry Chermette, and Christophe Morell
14.1 Introduction 361
14.2 Exploring Ground State Properties Thanks to Excited States 361
14.3 Exploring the Reactivity of Excited States with Excited States 371
14.4 Conclusion 375
15 Modeling the Photophysical Processes of Organic Molecular Aggregates with Inclusion of Intermolecular Interactions and Vibronic Couplings 379
WanZhen Liang, Yu-Chen Wang, Shishi Feng, and Yi Zhao
15.1 Introduction 379
15.2 Theoretical Approaches 381
15.3 Concluding Remarks 397
16 Duality of Conjugated Π Electrons 407
Yirong Mo
16.1 Introduction 407
16.2 The New Concept of Intramolecular Multibond Strain 412
16.3 Theoretical Method 413
16.4 Computational Analysis of the Concept of Intramolecular Multibond Strain 416
16.5 Experimental Evidence 422
16.6 Summary 426
17 Energy Decomposition Analysis and Its Applications 433
Peifeng Su
17.1 Introduction 433
17.2 Methodology 437
17.3 Applications of GKS-EDA 442
17.4 Conclusion 450
18 Chemical Concepts in Solids 455
Peter C. Müller, David Schnieders, and Richard Dronskowski
18.1 The Three Schisms of Solid-State Chemistry 455
18.2 Bloch’s Theorem 457
18.3 Basis Sets 460
18.4 Interpretational Tools 462
18.5 Applications 470
18.6 Summary 477
19 Toward Interpretable Machine Learning Models for Predicting Spectroscopy, Catalysis, and Reactions 481
Jun Jiang and Shubin Liu
19.1 Introduction 481
19.2 ML in a Nutshell 481
19.3 Chemistry-Based Descriptors as ML Features 485
19.4 Selected ML Applications 493
19.5 Concluding Remarks 507
20 Learning Design Rules for Catalysts Through Computational Chemistry and Machine Learning 513
Aditya Nandy and Heather J. Kulik
20.1 Computational Catalysis 513
20.2 Machine Learning (ML) in Catalysis 529
20.3 Summary 545
References 546
Index 559
